This document discusses approaches for studying disease causation through epidemiological studies. It outlines the difference between association and causation, describing various types of causal relationships like necessary vs sufficient. It also discusses guidelines for assessing causality, including temporal relationship, strength of association, biological plausibility, consistency of findings, and consideration of alternative explanations. The document uses examples like the relationship between Helicobacter pylori and duodenal ulcers to demonstrate how these guidelines can be applied to evaluate evidence for a causal inference.

1. From association to causation
deriving inference from
epidemiological studies
Sima Naderi, 2th year of MPH−department of epidemiology &
biostatistics, Kabul university of medical science

2. Presentation outline
• Introduction
• Approaches for studying disease etiology
• Type of Association
• Causal relationship
• Type of causal relationship
• Guidelines to asses causality
• Causal inference and conclusion
• Reference
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3. Why to know cause of events/disease
• As human being, Enable each of us to navigate our complex world
• As a doctor, why to know cause of disease?
• As a researcher?
• As an academic org member?
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4. Introduction
• Ascertainment of cause and effect relationships is one of the central
and most difficult tasks of all scientific activities
• Epidemiological principles stand on 2 basic assumption:
• Human disease does not occur at random.
• The disease and its cause as well as preventive factors can be identified by a
thorough investigation of population.
• Identification of relation (association, causation) between disease and
suspected risk factors forms major part of epidemiological research.
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5. Historical theories of disease causation
• Supernatural cause of “ and Karma
• Theory of humors (humor means fluid)
• The miasmatic theory of disease
• Theory of contagion
• Germ theory
• Koch`s postulations
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6. Approaches for studying disease etiology
• Expose animals to risk factors such as carcinogens in control lab
• Control the exposure dose
• Control other environmental conditions and genetic factors
• Keep lost to follow up to minimum
• Can we extrapolate data across species and from animal to human
population?
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7. Approaches for studying disease etiology
• Epidemiology build on unplanned or natural
experiments
• People exposes to risk factor for non- study purposes
• E.g. exposure to atomic bomb radiation in Hiroshima and
Nagasaki 1945
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8. Approaches for studying disease etiology
• Sequence of study in human population
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Randomized trial
Cohort studies
Case control studies
Available data
Clinical observation

9. Approaches for studying disease etiology
1.Determining
association
b/n an
exposure and
disease
Studies of group
characteristics:
ecologies studies
Studies of
individual
characteristics:
case-control,
cohort
2.If
association
exist
Causal
Non causal
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10. Association
• Concurrence of two variable more often, than would be expected by
chance.
• Correlation indicates the degree of Association.
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11. Type of association
• Spurious or artificial
• Real
• Non causal
• causal
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12. Spurious association
• Spurious association arise because of bias, when 2 variables are
improperly compared.
• E.g.
• Conclusion: prenatal mortality in hospital delivery is higher compared
to home delivery
• This conclusion results due to bias in study
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Study in England 5174 home delivery 11156 hospital delivery
Prenatal MR= 5.4/1000 Prenatal MR= 27.8/1000

13. Real(causal/noncausal) association
.
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14. Non causal association
• McMahon`s study: observed an association of coffee consumption
with risk of pancreatic cancer.
Causal association
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Coffee Drinking
Pancreatic Cancer
Coffee Drinking
smoking
pancreatic cancer
Non Causal association (due to
confounding)

15. Type of causal association
Direct
Indirect
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factor disease
factor diseaseStep
2
Step
1

16. Evidence for causal relationship
• Infectious disease: Henle assumptions 1840 which was expanded by
Koch in 1880s:
• The organism is always found with the disease
• The organism is not found with any other disease
• The organism, isolated from one who has the disease, and cultured through
several generations, produces the disease( in experimental animals)
• NCDs, no organism to detect and culture causal relationship more
complex
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17. Type of causal association
• Necessary and sufficient, (one to one relation, based on Koch theory)
Without that factor the disease never develops, and in its presence the
disease always develops
This situation rarely occurred
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Factor A disease
HIV AIDS

18. Type of causal association
• Necessary, not sufficient
• Factor is necessary but not sufficient to produce the disease
• Multiple factors are required, often in a specific temporal sequence
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Factor A
+
Factor B
+
Factor C
Disease

19. Necessary, not sufficient
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initiator
+
promoter
+
trigger
cancer

20. Type of causal association
• Sufficient, but not necessary
• The factor alone can produce the disease, but so can other factor
• Radiation, benzene – either can produce leukemia
• Cancer does not develop in everyone who has experienced radiation or benzene
exposure
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Factor A
or
Factor B
or
Factor C
Disease

21. Sufficient, but not necessary
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radiation
or
Benzene
exp
or
smoking
leukemia

22. Type of causal association
• Neither necessary nor Sufficient
• More complex model (independent.v=risk factor)
• Probably most accurately represents the causal relationships that operate in
most chronic disease
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Factor A + factor B
or
Factor C + factor D
or
Factor E + factor F
Disease

23. .
• Diabetics are most likely at risk of myocardial infarction than non diabetics
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2 matched groups
Myocardial
infraction
Risk factor
Non diabeticsdiabetics
diabetes

24. Guidelines for judging whether an association
is causal
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25. .
Guidelines
for inference
causal
association
temporal
Biological
plausibility
Alternative
explanation
Consistency
and
replication
Cessation
effects
Specificity
of the
association
Strength of
association
Dose-
response
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Major criteria
Minor criteria
Austin Bradford hill
1965

26. Temporal relationship
• Exposure to the factor must occurred before the disease developed
• Length of the interval between the exposure and outcome (asbestos
in lung cancer__15-20 year)
• Temporal relationship easily established in prospective cohort than in
case-control and retrospective cohort as
The only criteria that is inarguable
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27. Temporal relationship
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28. Dose-response relationship
• As dose of exposure increases, the risk of disease also increases
• If a dose-response relationship is present, it is strong evidence for a
causal relationship
• Absence of dose-response relationship dose not necessarily rule out a
causal relationship
• In some cases threshold may exist
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29. 2/27/2020 29

30. Strength of association
• Measured by
• OR
• RR
• The stronger association the more likely it is that the relation is causal
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31. Biological plausibility
• Coherence with the current body of biologic knowledge
• Sometimes, epidemiological observation preceded biologic
knowledge (mechanism of action, evidence from animal experiment)
• E.g. Gregg`s observation on rubella and congenital cataracts preceded any
knowledge of teratogenic viruses
• If epidemiological findings are not consistent with the existing
knowledge-interpreting the meaning of observed association might
be difficult
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32. Consideration of alternate explanation
• Explanations of relationship as a causal or due to confounding
• The extent to which the investigators have taken other possible
explanation into account and the extent to which they ruled out such
explanation are important considerations
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33. Cessation of exposure
• If a factor is a cause of a disease, the risk of disease is decline when
exposure to the factor is reduced or eliminated
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34. Consistency & Replication of findings
• If the relationship is causal, we would expect to find it consistency in
different studies (cohort, case-control) and in different populations.
• Causal association b/n smoking and lung cancer is found consistently
in:
• 50 retrospective studies
• 9 prospective studies
• Some times there are good reasons why study results differ. For
example, one study may have looked at low level exposure while
another looked at high level exposure.
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35. Specificity of the association
• Specificity implies a one to one relationship between the exposure
and outcome (weakest criteria).
• Not everyone who smokes develop lung cancer
• Not everyone who develops cancer has smoked
• Lack of specificity does not negate causation
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36. Additional model for causality
• Kennet rothman`s component cause theory: describe the
circumstances leading to a health outcome as being parts of one pie
chart, or a “causal pie”. without each component in place, the disease
or health outcome would not have occurred at that specific point in
time
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37. Slip on an icy sidewalk and break the wrist
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Causal pie
calcium intake impaired balance type of shoe Icy path fall

38. Directed acyclic graph
• One method used to create a conceptual diagram that maps the
relationship between the main exposure, outcome of intrest, and all
potential confounders for a given study.
• Confounders should identified for:
• Adjusting, less biased association
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Covariates
exposure outcome

39. Observed association & causal inference
• Could it be due
to bias
No
• Could it be
confounding
no • Could it be
result of chance
No
• Could it be
causal relation
yes • Apply
guidelines and
make judgment
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40. conclusion
• The causal inference resulted from the epidemiological studies are
very important to public health and provide inputs for political and
judicial decisions.
• E.g. the causal association b/n smoking and lung cancer has resulted
in labeling of cigarette packets and increased campaign ads.
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41. Wrong Causal inference
• Suppose a study find an association b/n paternal silk tie ownership
and infant mortality
• On the back of this, the government implements a program in which
5 silk ties are given to all men aged 18-45 with a view to reducing
infant mortality.
• We would all agree that this is madness
• This is because we understand the difference b/n association and
causation
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42. Assessment of the evidence suggesting helicobacter
pylori as a causative Agent of Duodenal ulcer
1. Temporal relationship About 11% of chronic gastritis patients duodenal occurs over a 10 year
period
2. Strength of association H.Pylori found - 90% of patients with duodenal ulcer
3. Dose-response R Density of H.Pylori per mm2 of gastric mucosa – higher in duodenal ulcer
patients
4. Replication of the findings Many of the observation – H.pylori – replicated repeatedly
5. Biological possibility • Earlier- difficult to invasion bacterium infecting the stomach antrum
causing ulcers in the duodenum, now recognized – H.pylori- binding
sites on antral cell.
• Induces mediators of inflammation
• Infected mucosa – weakened, susceptible to damaging effects of acid
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43. Assessment of the evidence suggesting helicobacter
pylori as a causative Agent of Duodenal ulcer
6. Cessation of
exposure
• Eradication – heals duodenal ulcers at the same rate as histamine
receptor antagonists
• Long-term ulcers recurrence rate – zero after H.pylori was eradicated
using triple – anti microbial therapy
7. Specific of
association
Prevalence of H.pylori in duodenal ulcers patients – 90% to 100%
8. Consistency
with other
knowledge
High prevalence of ulcer disease in later part of 19th century – consistent with
high prevalence of H.pylori due to poor living condition at the same period
9. Consideration
of alternative
explanation
Smoking risk of duodenal ulcer – H.pylori infected patients but not a risk
factor – H.pylori eradicated patients
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44. Reference
• Gordis leon. Textbook of epidemiology, 5th edition, chp 14, P243-260
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45. Thanks for attention
?
!
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